Abstract:
Antibody sequences can be determined at 99% accuracy directly from the polypeptide product by using bottom-up proteomics techniques. Sequencing accuracy at the peptide level is limited by the isobaric residues leucine and isoleucine, incomplete fragmentation spectra in which the order of two or more residues remains ambiguous due to lacking fragment ions for the intermediate positions, and isobaric combinations of amino acids, of potentially different lengths, for example, GG = N and GA = Q. Here, we present several updates to Stitch (v1.5), which performs template-based assembly of de novo peptides to reconstruct antibody sequences. This version introduces a mass-based alignment algorithm that explicitly accounts for mass coincidence errors. In addition, it incorporates a postprocessing procedure to assign I/L residues based on secondary fragments (satellite ions, i.e., w-ions). Moreover, evidence for sequence assignments can now be directly evaluated with the addition of an integrated spectrum viewer. Lastly, input data from a wider selection of de novo peptide sequencing algorithms are allowed, now including Casanovo, PEAKS, Novor.Cloud, pNovo, and MaxNovo, in addition to flat text and FASTA. Combined, these changes make Stitch compatible with a larger range of data processing pipelines and improve its tolerance to peptide-level sequencing errors.
摘要:
通过使用自下而上的蛋白质组学技术,可以直接从多肽产物以99%的准确度确定抗体序列。肽水平的测序准确性受到同量异位残基亮氨酸和异亮氨酸的限制。由于中间位置缺少碎片离子,其中两个或多个残基的顺序仍然不完整的碎片谱,和氨基酸的同量异位组合,可能不同的长度,例如,GG=N和GA=Q。这里,我们对Stitch(v1.5)进行了一些更新,其执行从头肽的基于模板的组装以重建抗体序列。此版本引入了基于质量的对齐算法,该算法明确说明了质量重合误差。此外,它结合了后处理程序,以根据次级碎片(卫星离子,即,w-ions)。此外,现在可以通过添加集成光谱查看器来直接评估序列分配的证据。最后,允许从更广泛的从头肽测序算法选择输入数据,现在包括卡萨诺沃,PEAKS,诺弗.云,pNovo,和MaxNovo,除了平面文本和FASTA。合并,这些变化使Stitch与更大范围的数据处理管道兼容,并提高了其对肽级测序错误的耐受性.